Papers
Learning the Irreducible Representations of Commutative Lie Groups
Taco Cohen, Max Welling
Learning Ordered Representations with Nested Dropout
Oren Rippel, Michael Gelbart, Ryan Adams
Active Learning of Parameterized Skills
Bruno Da Silva, George Konidaris, Andrew Barto
Nonnegative Sparse PCA with Provable Guarantees
Megasthenis Asteris, Dimitris Papailiopoulos, Alexandros Dimakis
Learning by Stretching Deep Networks
Gaurav Pandey, Ambedkar Dukkipati
Spectral Regularization for Max-Margin Sequence Tagging
Ariadna Quattoni, Borja Balle, Xavier Carreras et al.
Asynchronous Distributed ADMM for Consensus Optimization
Ruiliang Zhang, James Kwok
A Deep Semi-NMF Model for Learning Hidden Representations
George Trigeorgis, Konstantinos Bousmalis, Stefanos Zafeiriou et al.
Stochastic Gradient Hamiltonian Monte Carlo
Tianqi Chen, Emily Fox, Carlos Guestrin
Input Warping for Bayesian Optimization of Non-Stationary Functions
Jasper Snoek, Kevin Swersky, Rich Zemel et al.
Kernel Adaptive Metropolis-Hastings
Dino Sejdinovic, Heiko Strathmann, Maria Lomeli Garcia et al.
Scalable and Robust Bayesian Inference via the Median Posterior
Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin et al.
Structured Recurrent Temporal Restricted Boltzmann Machines
Roni Mittelman, Benjamin Kuipers, Silvio Savarese et al.
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits
Alekh Agarwal, Daniel Hsu, Satyen Kale et al.
Learnability of the Superset Label Learning Problem
Liping Liu, Thomas Dietterich
Multiresolution Matrix Factorization
Risi Kondor, Nedelina Teneva, Vikas Garg
On learning to localize objects with minimal supervision
Hyun Oh Song, Ross Girshick, Stefanie Jegelka et al.
Gaussian Approximation of Collective Graphical Models
Liping Liu, Daniel Sheldon, Thomas Dietterich
Adaptivity and Optimism: An Improved Exponentiated Gradient Algorithm
Jacob Steinhardt, Percy Liang
A Bayesian Framework for Online Classifier Ensemble
Qinxun Bai, Henry Lam, Stan Sclaroff
Weighted Graph Clustering with Non-Uniform Uncertainties
Yudong Chen, Shiau Hong Lim, Huan Xu
Online Stochastic Optimization under Correlated Bandit Feedback
Mohammad Gheshlaghi azar, Alessandro Lazaric, Emma Brunskill
Dynamic Programming Boosting for Discriminative Macro-Action Discovery
Leonidas Lefakis, Francois Fleuret
Riemannian Pursuit for Big Matrix Recovery
Mingkui Tan, Ivor W. Tsang, Li Wang et al.